Bisdas Sotirios1, Eleni Demetriou2, Cristian C Topriceanu3, Zosia Zakrzewska3. 1. Department of Neuroradiology, The National Hospital for Neurology and Neurosurgery, University College London NHS Foundation Trust, London, United Kingdom; Department of Brain Repair & Rehabilitation, Queen Square Institute of Neurology, University College London, London, United Kingdom. Electronic address: s.bisdas@ucl.ac.uk. 2. Department of Brain Repair & Rehabilitation, Queen Square Institute of Neurology, University College London, London, United Kingdom. 3. University College London Medical School, United Kingdom.
Abstract
PURPOSE: Gliomas are diagnosed and staged by conventional MRI. Although non-conventional sequences such as perfusion-weighted MRI may differentiate low-grade from high-grade gliomas, they are not reliable enough yet. The latter is of paramount importance for patient management. In this regard, we aim to evaluate the role of Amide Proton Transfer (APT) imaging in grading gliomas as a non-invasive tool to provide reliable differentiation across tumour grades. METHODS: A systematic search of PubMed, Medline and Embase was conducted to identify relevant publications between 01/01/2008 and 15/09/2020. Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) was used to assess studies' quality. A random-effects model standardized mean difference meta-analysis was performed to assess APT's ability to differentiate low-grade gliomas (LGGs) from high-grade gliomas (HGGs), WHO 2-4 grades, wild-type from mutated isocitrate dehydrogenase (IDH) gliomas, methylated from unmethylated O6-methylguanine-DNA methyltransferase (MGMT) gliomas. Area under the curve (AUC) of the Receiver Operating Characteristic (ROC) meta-analysis was employed to assess the diagnostic performance of APT. RESULTS: 23 manuscripts met the inclusion criteria and reported the use of APT to differentiate glioma grades with histopathology as reference standard. APT-weighted signal intensity can differentiate LGGs from HGGs with an estimated size effect of (-1.61 standard deviations (SDs), p < 0.0001), grade 2 from grade 3 (-1.83 SDs, p = 0.005), grade 2 from grade 4 (-2.34 SDs, p < 0.0001) and IDH wild-type from IDH mutated (0.94 SDs, p = 0.003) gliomas. The combined AUC of 0.84 highlights the good diagnostic performance of APT-weighted imaging in differentiating LGGs from HGGs. CONCLUSIONS: APT imaging is an exciting prospect in differentiating LGGs from HGGs and with potential to predict the histopathological grade. However, more studies are required to optimize and improve its reliability.
PURPOSE:Gliomas are diagnosed and staged by conventional MRI. Although non-conventional sequences such as perfusion-weighted MRI may differentiate low-grade from high-grade gliomas, they are not reliable enough yet. The latter is of paramount importance for patient management. In this regard, we aim to evaluate the role of Amide Proton Transfer (APT) imaging in grading gliomas as a non-invasive tool to provide reliable differentiation across tumour grades. METHODS: A systematic search of PubMed, Medline and Embase was conducted to identify relevant publications between 01/01/2008 and 15/09/2020. Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) was used to assess studies' quality. A random-effects model standardized mean difference meta-analysis was performed to assess APT's ability to differentiate low-grade gliomas (LGGs) from high-grade gliomas (HGGs), WHO 2-4 grades, wild-type from mutated isocitrate dehydrogenase (IDH) gliomas, methylated from unmethylated O6-methylguanine-DNA methyltransferase (MGMT) gliomas. Area under the curve (AUC) of the Receiver Operating Characteristic (ROC) meta-analysis was employed to assess the diagnostic performance of APT. RESULTS: 23 manuscripts met the inclusion criteria and reported the use of APT to differentiate glioma grades with histopathology as reference standard. APT-weighted signal intensity can differentiate LGGs from HGGs with an estimated size effect of (-1.61 standard deviations (SDs), p < 0.0001), grade 2 from grade 3 (-1.83 SDs, p = 0.005), grade 2 from grade 4 (-2.34 SDs, p < 0.0001) and IDH wild-type from IDH mutated (0.94 SDs, p = 0.003) gliomas. The combined AUC of 0.84 highlights the good diagnostic performance of APT-weighted imaging in differentiating LGGs from HGGs. CONCLUSIONS: APT imaging is an exciting prospect in differentiating LGGs from HGGs and with potential to predict the histopathological grade. However, more studies are required to optimize and improve its reliability.
Authors: Jinyuan Zhou; Moritz Zaiss; Linda Knutsson; Phillip Zhe Sun; Sung Soo Ahn; Silvio Aime; Peter Bachert; Jaishri O Blakeley; Kejia Cai; Michael A Chappell; Min Chen; Daniel F Gochberg; Steffen Goerke; Hye-Young Heo; Shanshan Jiang; Tao Jin; Seong-Gi Kim; John Laterra; Daniel Paech; Mark D Pagel; Ji Eun Park; Ravinder Reddy; Akihiko Sakata; Sabine Sartoretti-Schefer; A Dean Sherry; Seth A Smith; Greg J Stanisz; Pia C Sundgren; Osamu Togao; Moriel Vandsburger; Zhibo Wen; Yin Wu; Yi Zhang; Wenzhen Zhu; Zhongliang Zu; Peter C M van Zijl Journal: Magn Reson Med Date: 2022-04-22 Impact factor: 3.737